Evidence map›Paper›PMID 38964581›Full record

ArticleEnvironmental research2024

Estimating ambient air pollutant concentrations outside and inside homes in the Subpopulations and Intermediate outcomes in COPD air pollution (SPIROMICS air) cohort.

Kipruto Kirwa, Amanda J Gassett, Coralynn Sack, Laura M Paulin, Cheryl S Pirozzi, R Graham Barr, Prescott G Woodruff, MeiLan Han, May-Lin Wilgus, Igor Barjaktarevic and 3 more

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In one paragraph

Article in Environmental research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Kipruto KirwaDepartment of Environmental Health, Boston University School of Public Health, Boston, MA, USA. Electronic address: kirwa@bu.edu.
Amanda J GassettDepartment of Environmental and Occupational Health Sciences, University of Washington School of Public Health, Seattle, WA, USA.
Coralynn SackDepartment of Environmental and Occupational Health Sciences, University of Washington School of Public Health, Seattle, WA, USA.
Laura M PaulinDepartment of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Cheryl S PirozziDepartment of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
R Graham BarrDepartment of Medicine, Columbia University Medical Center, New York, NY, USA.
Prescott G WoodruffDepartment of Medicine, University of California, San Francisco, CA, USA.
MeiLan HanDepartment of Medicine, University of Michigan, Ann Arbor, MI, USA.
May-Lin WilgusDepartment of Medicine, David Geffen School of Medicine, Los Angeles, CA, USA.
Igor BarjaktarevicDepartment of Medicine, David Geffen School of Medicine, Los Angeles, CA, USA.
Stephen PetersDepartment of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA.
Nadia N HanselDepartment of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Joel D KaufmanDepartments of Environmental and Occupational Health Sciences, Epidemiology, and Medicine, University of Washington School of Public Health, Seattle, WA, USA.

Funding

XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI Joel Daniel Kaufman · 1995 to 2026
$42.5M
SPIROMICS II: Biological underpinnings of COPD heterogeneity and progressionU01HL137880 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WOODRUFF, PRESCOTT G · 2017 to 2021
$27.9M
SPIROMICS - Air Pollution StudyR01ES023500 · NIEHS · JOHNS HOPKINS UNIVERSITY · PI HANSEL, NADIA N, KAUFMAN, JOEL DANIEL · 2014 to 2018
$3.2M
The Role of Airway Morphology in Environmental LungDiseasesK23ES030725 · NIEHS · UNIVERSITY OF WASHINGTON · PI SACK, CORALYNN SHAYNA · 2019 to 2023
$835k
NHLBI NIH HHS HHSN268200900013CNHLBI NIH HHS HHSN268200900014CNHLBI NIH HHS HHSN268200900015CNHLBI NIH HHS HHSN268200900016CNHLBI NIH HHS HHSN268200900017CNHLBI NIH HHS HHSN268200900018CNHLBI NIH HHS HHSN268200900019CNHLBI NIH HHS HHSN268200900020CNHLBI NIH HHS U01 HL137880NIEHS NIH HHS K23 ES030725NIEHS NIH HHS P30 ES007033NIEHS NIH HHS R01 ES023500
6 · The paper itself

Abstract

backgroundValid, high-resolution estimates of population-level exposure to air pollutants are necessary for accurate estimation of the association between air pollution and the occurrence or exacerbation of adverse health outcomes such as Chronic Obstructive Pulmonary Disease (COPD).

objectivesWe produced fine-scale individual-level estimates of ambient concentrations of multiple air pollutants (fine particulate matter [PM

methodsTo estimate ambient concentrations, we used a hierarchical high-resolution spatiotemporal model that integrates hundreds of geographic covariates and pollutant measurements from regulatory and study-specific monitors, including ones located at participant residences. We modeled infiltration efficiency based on data on house characteristics, home heating and cooling practices, indoor smoke and combustion sources, meteorological factors, and paired indoor-outdoor pollutant measurements, among other indicators.

resultsCross-validated prediction accuracy (R

conclusionLeveraging well-validated fine-scale approaches for estimating outdoor, ambient-source indoor, and total indoor pollutant concentrations, we can provide comprehensive estimates of short and long-term exposure levels for cohorts undergoing follow-up in multiple different regions.

Indexed as

Air PollutantsAir Pollution, IndoorParticulate MatterPulmonary Disease, Chronic ObstructiveAgedCohort StudiesEnvironmental ExposureEnvironmental MonitoringFemaleHousingHumansMaleMiddle AgedUnited StatesAir PollutantsParticulate MatterAir pollutionCOPDExposure assessmentSpatiotemporal model

Identifiers

PMID38964581
PMCPMC11365799

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.